Mitochondrial citrate metabolism and efflux regulate BeWo differentiation

Cytotrophoblasts fuse to form and renew syncytiotrophoblasts necessary to maintain placental health throughout gestation. During cytotrophoblast to syncytiotrophoblast differentiation, cells undergo regulated metabolic and transcriptional reprogramming. Mitochondria play a critical role in differentiation events in cellular systems, thus we hypothesized that mitochondrial metabolism played a central role in trophoblast differentiation. In this work, we employed static and stable isotope tracing untargeted metabolomics methods along with gene expression and histone acetylation studies in an established BeWo cell culture model of trophoblast differentiation. Differentiation was associated with increased abundance of the TCA cycle intermediates citrate and α-ketoglutarate. Citrate was preferentially exported from mitochondria in the undifferentiated state but was retained to a larger extent within mitochondria upon differentiation. Correspondingly, differentiation was associated with decreased expression of the mitochondrial citrate transporter (CIC). CRISPR/Cas9 disruption of the mitochondrial citrate carrier showed that CIC is required for biochemical differentiation of trophoblasts. Loss of CIC resulted in broad alterations in gene expression and histone acetylation. These gene expression changes were partially rescued through acetate supplementation. Taken together, these results highlight a central role for mitochondrial citrate metabolism in orchestrating histone acetylation and gene expression during trophoblast differentiation.


Results
Differentiation alters metabolite abundance, energy charge, and glucose utilization. Throughout gestation, cytotrophoblasts fuse to form and renew syncytiotrophoblasts 4,5,8 . Prior work demonstrates cytotrophoblasts and syncytiotrophoblasts differ in their oxygen consumption rate 17,18 . However, it is unclear how differentiation impacts relative abundance of key glycolytic and TCA cycle intermediates and energy metabolites. Human BeWo cells have been used to elucidate the molecular mechanisms that regulate syncytia formation. In this model system, both biochemical and morphologic changes canonical to differentiation occur following treatment with the protein kinase A activator, forskolin (FSK) (Supplemental Fig. 1A) 19,20 . Biochemical differentiation describes the transcriptional changes and production of hormones such as human chorionic gonadotropin (HCG) key to syncytiotrophoblast function, whereas morphologic differentiation describes cell fusion resulting in syncytia formation. These aspects of trophoblast differentiation can be differentially regulated [21][22][23][24] . Forty-eight hours following treatment with forskolin, BeWo cells increase CGA , CGB2, and ERVW-1 gene expression (Supplemental Fig. 1B) and undergo morphological changes and increased fusion consistent with syncytialization (Supplemental Fig. 1C, D).
Given these initial observations of increased relative abundance of TCA cycle intermediates with differentiation, we investigated how differentiation impacts glucose utilization. Forty-eight hours following treatment of BeWo cells with DMSO or forskolin, we incubated cells with 17 mM uniformly 13 C-labeled glucose ([U-13 C 6 ]glucose) for 6 h and determined 13 C-enrichment relative to total pool size using an isotope tracing untargeted metabolomics approach (Fig. 1C). Both DMSO-and forskolin-treated cells rapidly metabolized glucose to pyruvate and lactate ( Fig. 1D) with approximately 50% of the total pool 13 C-enriched. Neither lactate nor pyruvate demonstrated forskolin-dependent changes in enrichment. However, approximately 30% of the DMSO-treated total citrate pool was 13 C-enriched and this enrichment increased to approximately 35% following forskolininduced differentiation (p < 0.01) (Fig. 1D). Glucose derived 13 C-enrichment into α-ketoglutarate and malate was lower than that of citrate, labeling 5% of the total pool size in DMSO-treated and 10% in forskolin-treated cells (p < 0.001). These differentiation-dependent changes in citrate, α-ketoglutarate, and malate 13 C-enrichment corresponded to the observed increases in total pool size (Fig. 1A) and suggest that TCA cycle remodeling accompanies differentiation.
To further examine the fate of glucose derived carbon during differentiation, we determined the ratio of the M + 2 isotopologue of malate to the M + 2 isotopologue of citrate, since this ratio depicts changes in the flux of glucose derived carbon through the TCA cycle (Fig. 1C). Trophoblast differentiation significantly increased this ratio suggesting increased forward flux of glucose into the second span of the TCA cycle (Fig. 1E). These findings suggest that undifferentiated cells export mitochondrial citrate to the cytoplasm, whereas differentiated cells retain relatively more citrate to support forward flux through the TCA cycle. These results may reflect activity of the citrate-malate shuttle via a "non-canonical" TCA cycle recently described in embryonic stem cells and myocytes 25,26 . Differentiation decreases expression of the mitochondrial citrate carrier. Import and export of metabolites through the inner mitochondrial membrane require mitochondrial transport proteins 12 . Specifically, the mitochondrial citrate carrier (CIC) is responsible for transporting citrate across the inner mitochondrial matrix into the cytoplasm in exchange for malate 27,28 . Following export of citrate across the inner mitochondrial matrix, it is converted to cytoplasmic acetyl-CoA through the action of ATP citrate lyase (ACLY www.nature.com/scientificreports/ cytoplasmic acetyl-CoA can be produced from acetate via ACSS2 ( Fig. 2A) 29,30 . Given that mitochondrial citrate efflux may be decreased with differentiation, we next quantified expression of CIC (encoded by SLC25A1) during differentiation at mRNA and protein levels. CIC and ACSS2 mRNA and protein levels both decreased following treatment with forskolin ( Fig. 2B-D). A decrease was not observed for ACLY. Similarly, SLC25A1 and ACSS2 mRNA expression decreased and ACLY expression remained unchanged in a trophoblast stem cell model following differentiation, indicating this difference in expression is not unique to BeWo cells (Supplemental Fig. 3) 31 . Overall, these results suggest that CIC regulates citrate export from mitochondria and partitions citrate and acetyl-CoA during differentiation.
Loss of mitochondrial citrate carrier impairs transcriptional reprogramming associated with differentiation. Prior work demonstrates that loss of citrate efflux impairs embryonic stem cell differentiation and that CIC is essential for early trophoblast function 25,32 . Given decreased citrate export and decreased CIC expression with differentiation, we next determined how loss of mitochondrial citrate carrier prior to differentiation impacts subsequent trophoblast differentiation. Using a CRISPR-Cas9 system 33 , transduction of three distinct guides targeting SLC25A1 resulted in complete loss of CIC protein expression compared to empty vector and scrambled non-targeting guide RNA (gRNA)-treated controls (Fig. 3A). We subsequently report results from two control and two knockout lines for most assays. To test the impact of CIC on biochemical differentiation, HCG production and gene expression were assessed. HCG following forskolin treatment was 50% lower in CIC KO cells compared to control cells (Fig. 3B). Loss of CIC decreased mRNA expression of CGA, CGB2, ERVW-1, and ERVFRD-1 by approximately 60% upon differentiation (Fig. 3C). To test the impact of CIC on morphologic syncytialization, BeWo cells were plated on coverslips and stained for E-cadherin and HCG fol-  www.nature.com/scientificreports/ lowing DMSO or forskolin treatment. HCG intracellular staining is observed in forskolin-treated CIC knockout cells, despite detected differences in transcript expression and secreted protein concentrations, consistent with finding that HCG is produced following loss of CIC though likely to a lesser degree than control cells. Loss of CIC did not impair morphologic syncytialization (Supplemental Fig. 5), suggesting that CIC uncouples biochemical and morphologic differentiation. Given these initial observations highlighting impairments in biochemical differentiation, RNA sequencing was performed following treatment of control or CIC knockout BeWo cells with forskolin or DMSO vehicle. As expected, treatment with forskolin caused dramatic changes in mRNA abundances accounting for 68% of the variance represented by the first principal component (PC1), while loss of CIC is represented within the second principal component (PC2) accounting for 11% of the variance (Fig. 4A). Vehicle-treated control and CIC knock-out cells have similar expression along PC1 whereas treatment with forskolin caused a larger shift for control cells compared to the knock-out cells along PC1, consistent with the observations above suggesting that loss of CIC compromises differentiation. Next, we used differential expression analysis to identify genes affected by CIC loss. We found 23 genes differentially expressed due to CIC loss in vehicle-treated cells and 88 genes differentially expressed due to CIC loss in forskolin-treated cells using absolute fold change of 1.5, p adjusted < 0.01 ( Fig. 4B, C, Supplemental Table 1). Using pathway analysis of genes differentially expressed upon treatment with www.nature.com/scientificreports/ forskolin, loss of CIC decreased expression in pathways that regulate metabolic processes, reproductive system development, and female pregnancy and increased expression in pathways that regulate cytoskeletal reorganization (Fig. 4D). Further assessment of these pathways indicated that many observed differences were driven by genes involved in differentiation. Specifically, loss of CIC impaired up-regulation of CGA, CGB2, HSD11B2, ERVW-1, and ERVFRD-1 and impaired down-regulation of genes maintaining cytotrophoblasts including TP63 and ITGA6 following forskolin treatment (Fig. 4E). Alterations in expression of these genes in control and CIC KO were selectively confirmed using qPCR (Fig. 4F).

Loss of CIC dysregulates histone acetylation.
Prior work demonstrates that histone deacetylation is required for trophoblast differentiation, with global decreases in histone acetylation observed following differentiation in primary trophoblasts, trophoblast stem cells, and BeWo cells 30 . Using ChIP sequencing, decreased histone acetylation was observed at genes traditionally associated with cytotrophoblastic state and increased histone acetylation was observed at genes associated with differentiated states 11 . While histone deacetylases 1 and 2 regulate these deacetylation events, how changes in acetyl-CoA substrate availability impact this process in trophoblasts remains unknown. Given the broad changes in gene expression observed with loss of the mitochondrial citrate carrier, we assessed CIC's impact on histone acetylation during trophoblast differentiation. Similar to prior results, differentiation decreased global histone acetylation and acetylation at lysine 9 in control cells (Fig. 5A, B). Strikingly, loss of CIC impaired total histone H3 and lysine 9 deacetylation following forskolin treatment ( Fig. 5A, B). No statistically significant difference in H3 lysine 27 acetylation in control or CIC knockout cells was detected with differentiation. Overall, this suggests that loss of CIC impacts histone acetylation during differentiation. However, we cannot discern if this is due directly to loss of mitochondrial citrate efflux or due to impaired differentiation. www.nature.com/scientificreports/ Acetate partially rescues gene expression following differentiation. Citrate export across the inner mitochondrial membrane contributes to the acetyl-CoA pool required for histone acetylation through the actions of ATP-citrate lyase (encoded by ACLY). Acetate may also be converted to acetyl-CoA through ACSS2 in the cytoplasm to support histone acetylation. We assessed whether acetate could rescue the dysregulated differentiation observed in CIC knockout cells. To do this, control and CIC knockout cell lines were treated with 1 mM acetate and the expression of key differentiation markers was quantified via qPCR. While acetate rescued expression of CGA , CGB2 and ERVW-1, it did not rescue expression of HSD11B2 or ERVFRD-1 (Fig. 6). This www.nature.com/scientificreports/ partial rescue suggests that loss of mitochondrial citrate export may have locus-specific effects and that cytoplasmic acetyl-CoA may be a critical mediator of impaired differentiation following loss of CIC.

Loss of mitochondrial citrate efflux alters metabolic reprogramming during differentiation.
Given that addition of acetate did not fully rescue differentiation in CIC knockout cells, we next assessed how loss of CIC impacts TCA cycle metabolites following differentiation using high-resolution LC-MS. Assessment of static total cellular pools of metabolites following treatment with DMSO showed that loss of CIC decreased citrate, aconitate, and aspartate in vehicle-treated cells compared to empty vector or scrambled gRNAtreated control cells. However, loss of CIC did not result in statistically significant differences in α-ketoglutarate, fumarate, malate, or acetyl-CoA in vehicle-treated cells. Following forskolin treatment, loss of CIC decreased citrate, aconitate, and aspartate compared to control cells (Fig. 7A). However, no CIC-dependent differences were observed in α-ketoglutarate, fumarate or malate abundance compared to empty vector or scrambled gRNAtreated control cells in forskolin-treated conditions. Surprisingly, total cellular acetyl-CoA pool sizes were preserved in CIC knockout cells and increased with forskolin treatment, which may reflect increased mitochondrial localization of acetyl-CoA or other metabolic adaptations within cells.
Isotope tracing untargeted metabolomics with [U-13 C 6 ]glucose was performed to determine how loss of citrate efflux impacts incorporation of 13 C-label into TCA cycle metabolites. Both control and CIC knockout cells readily incorporated glucose-derived carbon into pyruvate to similar levels across all conditions (Fig. 7B). With differentiation, 13 C-enrichment of citrate increased in control cells (Fig. 7C) consistent with results shown in Fig. 1E. However, the forskolin-induced increased citrate enrichment observed in control-gRNA cells was not www.nature.com/scientificreports/ observed in CIC knockout cells following differentiation and the total 13 C-enrichment was lower than forskolintreated, empty vector or scrambled gRNA-treated control cells. This decreased enrichment correlated with the smaller citrate pool size observed with CIC knockout (Fig. 7A). Additionally, while differentiation increased malate enrichment in both control and CIC knockout cells, lower total enrichment was found following forskolin treatment of CIC knockout cells (Fig. 7D). Given that loss of CIC does not diminish total malate pool size, this decrease in malate 13 C-enrichment likely reflects metabolic compensation from anaplerotic sources other than glucose-sourced pyruvate, e.g., amino acids. Finally, to examine the impact of differentiation on flux of glucose-derived carbon into the second span of the TCA cycle, we examined the ratio of M + 2 malate to M + 2 citrate following loss of CIC. In control cells, the M + 2 malate to M + 2 citrate ratio increased following forskolin stimulation, suggesting increased incorporation of glucose-derived carbon into the second span of the TCA cycle (Fig. 7E). In CIC knockout cells, the M + 2 malate to M + 2 citrate ratio also increased, but to a smaller extent than observed in empty vector or scrambled gRNAtreated control cells. Combined, these findings demonstrate that loss of CIC contributes to metabolic adaptation and its absence decreases forward flux of glucose-derived citrate through the TCA cycle with differentiation.

Discussion
Trophoblast differentiation requires coordinated metabolic, transcriptional, and epigenetic reprogramming. Our results are the first to demonstrate that trophoblast differentiation is associated with changes in citrate metabolism and that loss of mitochondrial citrate export impairs differentiation with dysregulation of histone acetylation potentially playing a role. Overall, our work highlights specific metabolic differences occurring with differentiation and identifies the mitochondrial citrate carrier as a regulator of trophoblast differentiation.
Prior work highlights differences in cytotrophoblast and syncytiotrophoblast metabolism using Seahorse respirometry 17,18 . Our work specifically demonstrates that differentiation is associated with increased ATP concentration and increased TCA cycle metabolite abundance and enrichment from 13 C-labeled glucose. Based on our carbon tracing studies, undifferentiated BeWo cells efflux mitochondrial citrate to a greater extent than differentiated BeWo cells, whereas differentiated BeWo cells preferentially retain citrate within the TCA cycle to a greater extent. This is consistent with recent reports highlighting a "non-canonical" TCA cycle in undifferentiated cells likely reflecting the activity of the citrate-malate shuttle necessary to sustain cytoplasmic acetyl-CoA pools in undifferentiated states to one supporting ATP generation following differentiation 25 . Surprisingly, loss of mitochondrial citrate efflux decreased total citrate abundance, but not α-ketoglutarate or malate. Additionally, the M + 2 malate to M + 2 citrate ratio was not increased following loss of citrate efflux via CIC knockout. www.nature.com/scientificreports/ Together, this suggests that other anaplerotic sources such as glutamine may contribute to TCA cycle intermediates following loss of citrate efflux. Acetyl-CoA cannot be transported across the mitochondrial inner membrane, thus citrate is a key metabolic intermediate through which carbon obtained from glucose metabolism contributes to cytoplasmic acetyl-CoA pools. Once in the cytoplasm, ACLY converts citrate to acetyl-CoA which can be used for histone acetylation 34 . The increased citrate and acetyl-CoA with differentiation likely reflect an increase in mitochondrial metabolite pool size. Mitochondrial compartmentalization of citrate and acetyl-CoA may decrease substrate availability for histone acetylation. While our studies do not formally delineate metabolite location, defining the spatial-temporal regulation of acetyl-CoA pools involved in nuclear signaling events remains of interest for future investigation 35,36 .
While acetyl-CoA pool sizes are preserved in CIC knockout cells despite lower abundance of cellular citrate, it is unclear if this is due to increased acetyl-CoA compartmentalization or the result of other metabolic adaptations. Application of exogenous acetate partially rescues gene expression in CIC knockout cells, suggesting that cytoplasmic acetyl-CoA may be dysregulated in CIC knockout cells. In other systems, loss of ACLY is associated with increased expression of ACSS2, and increased ACSS2 activity cannot be excluded in CIC knockout cells 30 . While loss of CIC impairs histone de-acetylation following differentiation, our work cannot delineate if this is the cause or result of impaired differentiation following loss of citrate efflux. Trophoblast differentiation is associated with decreased total histone acetylation but increased histone acetylation near loci associated with syncytiotrophoblasts and decreased acetylation at loci associated with cytotrophoblasts 11 . We observed global changes in histone acetylation following loss of mitochondrial citrate export and postulate that loss of citrate efflux impairs locus-specific regulation resulting in the observed impairments in trophoblast differentiation. Future work will investigate how loss of citrate efflux impacts locus-specific regulation of gene expression during trophoblast differentiation.
This work focuses on how citrate may regulate gene expression through its action on acetyl-CoA pools and potentially histone acetylation. It is possible that changes in other metabolites such as α-ketoglutarate may impact histone methylation events and contribute to changes in gene regulation. α-ketoglutarate is a key cofactor required for demethylation by Jumanji demethylases and histone demethylation regulates trophoblast differentiation 37,38 . Additionally, the impact of other metabolic nodes such as glutamine, glutamate, fatty acids, and carnitines may facilitate adaptation to impaired mitochondrial citrate efflux 36 . Future work will define how mitochondrial nutrient flux regulates histone acetylation and methylation events and whether changes in carbon sources specifically regulate this process.
One surprising finding is that loss of CIC impairs HCG production and broadly impacts expression of multiple genes involved in trophoblast differentiation; yet, we were unable to detect differences in morphologic syncytialization with forskolin treatment. Several prior studies have identified distinct regulators of biochemical and morphologic syncytialization, including transcription factors and differential activators of protein kinase A and C and mitogen-activated protein kinases (MAPK) pathways [21][22][23][24] . At this time, we speculate that loss of CIC may impact expression or activation of specific transcription factors or signaling pathways that regulate these two distinct aspects of trophoblast differentiation. Future work will be directed toward defining these pathways.
BeWo cells represent an established model to study syncytiotrophoblast differentiation and exhibit forskolininduced changes in gene expression and hormone production similar to primary trophoblasts 19,39,40 . However, the BeWo model may not fully recapitulate all aspects of trophoblast differentiation. For instance, BeWo cells contain an abnormal number of chromosomes and originate from a male placenta, which may influence cellular metabolism and gene expression 41 . However, similar expression in SLC25A1, ACSS2, and ACLY were observed in male-derived trophoblast stem cells. Additionally, our finding of decreased histone acetylation upon differentiation is similar to prior work that demonstrates differentiation-dependent decreases in histone acetylation among primary trophoblasts, trophoblast stem cells, and BeWo cells 11 . Finally, our metabolic data aligns with work by others that suggests syncytiotrophoblasts are more metabolically active than cytotrophoblasts 18 .
Overall, this work provides evidence that mitochondrial citrate metabolism is regulated during differentiation and that differentiation is associated with decreased citrate efflux and increased forward flux through the TCA cycle. Loss of CIC results in impaired biochemical differentiation and broad changes in gene expression, though does not impair morphologic differentiation. Though the specific mechanisms of this gene dysregulation remain unclear, abnormalities in histone deacetylation may contribute to the broad gene expression differences. Collectively, this work highlights roles beyond ATP generation for mitochondria in trophoblasts and identifies mitochondrial citrate efflux as a key regulator of trophoblast differentiation.  Hs-GCM1-Forward  IDT  CCG TAA GAA GTT AGA AGC CCT   Hs-GCM1-Reverse  IDT  TCG ACT CCC CTC AGA AAT GC   Hs-ERVFRD-1-F1  IDT  CGG ATA CCT TCC CTA GTG CCAT   Hs-ERVFRD-1-R1  IDT  ACA GCT TCA CTT GGG TGT GA   Hs_TEAD4_F  IDT  CAG TAT GAG AGC CCC GAG AA   Hs_TEAD4_R  IDT  TGC TTG AGC TTG TGG  www.nature.com/scientificreports/ Trophoblast stem cells (TSC, clone CT-29) were maintained in DMEM/F12 basal media containing with 100 µg/ml primocin, 0.15% BSA, 1% ITS-X, 1% Knockout Serum Replacement and 0.2 mM ascorbic acid and supplemented with 2.5 µM Y27632, 25 ng/ml EGF, 0.8 mM Valproic Acid, 5 µM A83-01, and 2 µM CHIR99021 on iMatrix-511 coated plates to maintain cells in self-renewing state. Cells were cultured at 37C, 5% CO2. To induce differentiation, 100,000 cells were plated on a 6 well plate coated with iMatrix-511 in self-renewing media. On day 1, media was replaced with DMEM/F12 basal media containing 100 µg/ml Primocin, 0.1% BSA, 1% ITS-X supplemented with 2.5 µM Y27632, 4% KSR, and 2 µM forskolin to induce differentiation. Self-renewing cells were maintained in self-renewing media. On day 3 following differentiation, RNA was isolated for qPCR.

Methods
Generation of SLC25A1 knockout cell lines. To generate CIC knockout BeWo cells, CRISPR guide RNAs (gRNAs) targeting exon 1 of SLC25A1 were subcloned into lentiCRISPR v2 (Addgene Plasma 52961) using BbsI sites as described 33,42 . Non-targeting guides were generated using previously reported sequences. Lentivirus was made by transfecting LentiX Cells (Takara) with lentiCRISPRv2 vector including guide of interest, psPAX2 (Addgene plasmid #12260) and pMD2.G (Addgene plasma #12259) using Fugene transfection reagent (Promega) in DMEM containing 10% FBS and Pen/Strep. 24 h after transfection, additional FBS was added to a final concentration of 30%. Virus containing media was harvested 72 h after transfection, centrifuged to remove cellular debris and passed through a 0.45 µM filter (Pall Corporation). 1 ml of virus containing media was mixed with 1 ml of F12K and 1 µg/ml polybrene and added to BeWo cells plated 1 day prior to transduction. Forty-eight hours after transduction, selection was started with 1 µg/ml puromycin and 1 mM acetate was added to media to support cell growth. Complete loss of CIC expression took approximately 12 days, likely due to slow turnover of mitochondrial transport proteins. After confirmation of CIC knockout, cells were used experimentally on days 14-28. Cells were maintained in culture in F12K:DMEM supplemented with 1 mM acetate. However, all differentiation experiments were done without supplemental acetate unless otherwise indicated.

Metabolomic profiling and isotope tracing metabolomics. Cell treatments and harvesting. 250,000
BeWo cells were plated and twenty-four hours after plating, media was changed and cells were treated with 40 µM Forskolin or DMSO. Forty-eight hours after initiation of treatment, cells were harvested for static metabolomics analysis. For isotope tracing metabolomics, cells were incubated with F12K and DMEM media supplemented with 17 mM [U-13 C 6 ]glucose (Cambridge Isotopes) or unlabeled naturally occurring glucose (Sigma) (standard concentration in F12K/DMEM media) for 6 h. A mirror plate was maintained for each condition to facilitate normalization to total protein. After treatment, samples were collected by washing twice with ice cold PBS, once with ice cold water and snap freezing in liquid nitrogen prior to transferring cells in methanol to a fresh tube. Solvent was evaporated and samples stored at -80 °C until ready for analysis.
Prior to analysis, metabolites were extracted by adding 1000 µl of 2:2:1 (v:v:v) Acetonitrile (AcN):Water(H 2 O):MeOH as previously described 43,44 . Samples underwent three rounds of vortexing, sonication and snap freezing in liquid nitrogen. The samples were incubated at − 20 °C for 1-4 h, spun to remove proteins, transferred to fresh tube, evaporated, and reconstituted in 40 μl of 1:1 (v:v) AcN:H 2 O. Prepared samples were vortexed, sonicated, centrifuged, and analyzed. All analyses were performed on Thermo Vanquish liquid chromatograph hyphenated with Thermo Q-Exactive Plus mass spectrometer equipped with heated ESI (HESI) source.
Relative abundance of glycolytic and TCA cycle intermediates. To identify selected TCA cycle and glycolytic metabolites, samples were analyzed using Atlantis Premier BEH Z-HILIC Column (2.1 mm × 100 mm, 1.7 μm). Separation was complete using Mobile phase A (15 mM ammonium bicarbonate in water, pH 9.0) and Mobile Phase B (15 mM ammonium bicarbonate pH, 9.0 with 90% AcN) using the following gradients: 10% Mobile Phase A for 5 min, 35% Mobile Phase A for 2 min and 10% Mobile Phase A for 3 min. Separations were performed at a flow rate 0.5 to 1 ml/min, column temperature at 30 °C and an injection volume of 2 μl. The mass spectrometer operated in negative mode using full scan (FS) mode (m/z 68-1020) with optimized HESI source conditions: auxiliary gas 10, sweep gas 1, sheath gas flow at 30 (arbitrary unit), spray voltage − 4 kV, capillary temperature 350 °C, S-lens RF 50, and auxiliary gas temperature 350 °C. The automatic gain control (AGC) target was set at 3e6 ions and resolution was 70,000.
Xcalibur Quan Browser was used for peak identification and integration. Metabolite profiling data was analyzed with QuanBrowser using standard verified peaks and retention times. Metabolite peak identity was confirmed based on retention time, m/z and compared to authentic internal standards as previously described 44,45 . Integrated signal for each metabolite was normalized to total protein determined using Bicinchoninic Acid Assay (BCA) on mirror plates for each condition. All protein normalized signal intensity was then normalized to DMSO control conditions and differences in relative abundance determined.
Isotope tracing untargeted metabolomics. For isotope tracing experiments, following metabolite extraction, 20 mM of ammonium phosphate was added to each sample and samples were analyzed using on a SeQuant ZIC-pHILIC (Merc) column (150 mm × 2.1 mm) as previously described [44][45][46] . Briefly, separation was performed using binary gradients of mobile phase A (10 mM Ammonium acetate/ammonium hydroxide, pH 9.0, 95% water/5% AcN) and mobile phase B (AcN). The following gradients were used: 100-0% B for 50 min, 0% B for 7 min and 100% B for 13 min. Flow rate was set to 0.2 ml/min, column temperature was 45 °C, and injection volume was 2 µl. The mass spectrometer operated in negative mode using full scan (FS) mode (m/z 68-1020) using optimized HESI source conditions: auxiliary gas 10, sweep gas 1, sheath gas flow at 30 (arbitrary unit), spray voltage − 4 kV, capillary temperature 350 °C, S-lens RF 50, and auxiliary gas temperature 350 °C. The automatic gain control (AGC) target was set at 3e6 ions and resolution was 70,000. www.nature.com/scientificreports/ Compound Discoverer 3.1(Thermo) was used for peak identification, integration and natural abundance correction. Briefly, negative mode data processing used the following parameters: 5 ppm mass tolerance, 1 min maximum retention drift time, minimum scans per peak of 5 and maximum peak width of 0.5 min. Background signals were excluded based on the Sample/Blank signal ratio > 3. Percent (%) enrichment was determined for each metabolite of interest. For poorly integrated peaks, Xcalibur was used for isotopologue peak identification and integration following natural abundance correction by IsoCorrectoR 47 .
Energy metabolite quantification. To quantify energy metabolites using methods described in 48,49 , cell pellets were treated with 0.4 M perchloric acid, 0.5 mM EGTA extraction solution containing [ 13 C 10 , 15 N 5 ]ATP sodium salt (100 μM), [ 13 C 10 , 15 N 5 ]AMP sodium salt (100 μM), and [1,2-13 C 2 ]acetyl-CoA lithium salt (5 μM)) as internal standards, all purchased from Sigma. Samples underwent three rounds of vortexing, snap freezing in liquid nitrogen, and sonication. Following 10 min incubation on ice, samples were centrifuged and supernatants was neutralized with 0.5 M K 2 CO 3 . Following additional centrifugation, extracts were analyzed by LC-MS/MS as previously described and normalized to total protein for each condition 48,49 . Quantitative PCR. Total RNA was extracted from cells using the Quick-RNA MiniPrep protocol provided by the kit's manufacturer (Zymo) and 1 µg of RNA was used to synthesize cDNA (iSCRIPT, BioRad). For quantitative real time PCR, reactions were carried out using SsoAdvanced Universal SYBR Green Supermix (BioRad) on a CFX384 Real-Time System (Bio-Rad). Transcripts were quantified using the 2 −ΔΔCT method. and normalized to cyclophiln. Primer sequences are listed in Key Resources. RNA 6 Million average per sample) were trimmed using Trimmomatic (v0.33) enabled with the optional "-q" option; 3 bp sliding-window trimming from 3′ end requiring minimum Q30. Quality control was completed by FastQC. Read mapping was performed via Hisat2 (v2.1.0) using the human genome (GRCh38) as reference. Gene quantification of Ensembl v97 annotations was completed using Subread. Counts were normalized using the median ratio method and differentially expressed genes were identified using the Wald test in DeSeq2 50 . The Benjamini and Hochberg method was used to account for False Discovery Rate in DeSeq2 and give an adjusted p. Genes with an adjusted p-value ≤ 0.01 were considered statistically significant. PCA plots were made using ggplot2 51 , volcano plots made using EnchanedVolcano 52 , and Pathway analysis completed using cluterProfiler 53 in R(v4.2.1). RNA Sequencing Data has been deposited at NCBI (GEO accession number GSE223514).

RNA-sequencing.
Protein expression. Following treatment, cells were washed with ice cold phosphate buffered saline (PBS) and lysed using 250 µl of RIPA Buffer (Sigma) supplemented with 1× Protease Arrest inhibitor. For assessment of histone acetylation, 1× HDAC inhibitor (Active Motif) was added to lysis buffer, and cells were sonicated for 45 s with 3 s pulses at power of 30% on ice. Lysates were centrifuged for 5 min at 4 °C at 21,000 × g. Bicinchoninic Acid Assay (Sigma) was used to determine protein concentration. 5 µg of protein was used for histone expression and 30 µg of protein was used to detect expression of other proteins. Lysates were run on 4-12% or 10% Bis-Acrylamine precast gels (Invitrogen) and transferred to nitrocellulose. Membranes were blocked with 2% bovine serum albumin (Sigma) or 5% milk in tris buffered saline (TBS) and stained overnight at 4 °C with primary antibodies (see key resources). Blots were washed with TBS and stained with HRP-tagged secondary antibodies. Blots were developed using SuperSignal West Pico PLUS Chemiluminescent Substrate (Thermo). Total protein loading was assessed by BlotFastStain (G-Biosciences). Blots were imaged using Bio-Rad CheiDoc MP imaging system and band density was quantified using ImageJ.
Imaging. 50,000 BeWo cells were plated on poly-l-lysine treated glass coverslips coated with 10% FBS in a 24-well plate. At 24 h, media was replaced and cells were treated with 40 µM forskolin or DMSO as vehicle control. At 48 h, wells were washed with PBS and were fixed with 4% paraformaldehyde (Electron Microscopy Services) for 10 min at 37 °C. Wells were washed again twice with PBS, then each coverslip was moved to a staining box. The cells were permeabilized with 0.1% TritonX (Sigma) and incubated for 10 min at room temperature. The coverslips were again washed twice with PBS, then incubated with 5% goat serum at room temperature. After one hour, coverslips were washed twice with PBS then incubated with mouse E-cadherin (BD Biosciences) and rabbit monoclonal HCG (Abcam) primary antibodies (Abcam) (diluted 1:200) overnight at 4 °C protected from light. The following day, the coverslips were washed three times with PBS and incubated with mouse and rabbit secondary antibodies (Abcam) (diluted 1:400) for 1 h, protected from light at room temperature. Coverslips were washed with PBS, dipped in MilliQ water, and placed on slides with Prolong Glass Antifade Mounting Media with DAPI (Invitrogen). Slides were allowed to dry overnight and then sealed using clear nail polish. Coverslips were kept at − 20 °C until imaging. Images were acquired on an Olympus FluoView BX2 Upright Confocal at the University of Minnesota Imaging Core. Using ImageJ, Percent fusion was quantified as the # of nuclei in syncytia divided by the total # of nuclei multipled by 100%. Quantification and statistical analysis. The Student's t test was used when comparing the means of two groups after a limited number of statistical outliers were excluded following identification by the Grubbs test. ANOVA was used to compare the means of more than two groups. p values less than 0.05 were considered statistically significant. Data were organized and analyzed using Microsoft Excel and GraphPad Prism.